摘要
针对基本混合蛙跳算法的缺陷,提出了一种基于混沌优化策略的改进混合蛙跳算法(SFLA)。在青蛙更新策略中引入自适应扰动机制,平衡了算法搜索深度,并利用高斯变异算子代替随机更新操作,提高了算法搜索速度;在全局迭代中借鉴混沌优化策略思想,以概率形式对最优个体进行优化,避免了族群陷入局部最优,并证明了改进算法以概率1收敛于全局最优解。最后用MATLAB对测试函数进行了仿真,仿真结果表明改进的混合蛙跳算法在收敛速度、优化精度上有较大改善。
Based on the problems of the shuffled frog leaping algorithm（SFLA）,this paper presented the improved SFLA.It proposed the mechanism based on mutation idea in differential evolution in order to balance algorithm search depth,and adop-ted Gaussian mutation to replace the original SFLA update strategy,which improved the convergence speed.Based on the chaos optimization strategy,it optimized the best solution in the form of probability,and avoided local optimum.It proved the improved SFLA to be converged to the global optimization solution with probability one.Finally with MATLAB,it implemented test function simulations.The simulation results show that the improved SFLA has better performance in the convergence speed and optimization precision.
出处
《计算机应用研究》
CSCD
北大核心
2013年第6期1708-1711,共4页
Application Research of Computers
基金
河南省基础与前沿技术研究基金资助项目(112300410225)
河南省重点攻关基金资助项目(112102210408)
关键词
混沌优化策略
混合蛙跳算法
收敛性
MATLAB
chaos optimization strategy
shuffled frog leaping algorithm（SFLA）
convergence
MATLAB
